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About Mathematics of Deep Learning Introduction - Leonid Berlyand
This document provides an introduction to the book "Mathematics of Deep Learning" by Leonid Berlyand and Pierre-Emmanuel Jabin. The book aims to provide a mathematical perspective on key elements of deep neural networks (DNNs), emphasizing underlying mathematical ideas. It introduces basic concepts from deep learning such as DNN definitions, loss functions, backpropagation, and convolutional neural networks in a rigorous yet accessible mathematical way. The book is based on courses taught by the authors and focuses on explaining deep learning techniques through simple examples and definitions.
Detailed Information
| Author: | ['DEV 9-T'] |
|---|---|
| Publication Year: | 2023 |
| Pages: | 134 |
| Language: | English |
| Format: | |
| Price: | FREE |
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